Sustainable development

Tech giants back Trump’s AI deregulation plan amid public concern over societal impacts

Donald Trump recently hosted an AI summit in Washington, titled ‘Winning the AI Race,’ geared towards a deregulated atmosphere for AI innovation. Key figures from the tech industry, including Nvidia’s CEO Jensen Huang and Palantir’s CTO Shyam Sankar, attended the event.

Co-hosted by the Hill and Valley Forum and the Silicon Valley All-in Podcast, the summit was a platform for Trump to introduce his ‘AI Action Plan‘, comprised of three executive orders focusing on deregulation. Trump’s objective is to dismantle regulatory restrictions he perceives as obstacles to innovation, aiming to re-establish the US as a leader in AI exportation globally.

The executive orders announced target the elimination of ‘ideological dogmas such as diversity, equity, and inclusion (DEI)’ in AI models developed by federally funded companies. Additionally, one order promotes exporting US-developed AI technologies internationally, while another seeks to lessen environmental restrictions and speed up approvals for energy-intensive data centres.

These measures are seen as reversing the Biden administration’s policies, which stressed the importance of safety and security in AI development. Technology giants Apple, Meta, Amazon, and Alphabet have shown significant support for Trump’s initiatives, contributing to his inauguration fund and engaging with him at his Mar-a-Lago estate. Leaders like OpenAI’s Sam Altman and Nvidia’s Jensen Huang have also pledged substantial investments in US AI infrastructure.

Despite this backing, over 100 groups, including labour, environmental, civil rights, and academic organisations, have voiced their opposition through a ‘People’s AI action plan’. These groups warn of the potential risks of unregulated AI, which they fear could undermine civil liberties, equality, and environmental safeguards.

They argue that public welfare should not be compromised for corporate gains, highlighting the dangers of allowing tech giants to dominate policy-making. That discourse illustrates the divide between industry aspirations and societal consequences.

The tech industry’s influence on AI legislation through lobbying is noteworthy, with a report from Issue One indicating that eight of the largest tech companies spent a collective $36 million on lobbying in 2025 alone. Meta led with $13.8 million, employing 86 lobbyists, while Nvidia and OpenAI saw significant increases in their expenditure compared to previous years. The substantial financial outlay reflects the industry’s vested interest in shaping regulatory frameworks to favour business interests, igniting a debate over the ethical responsibilities of unchecked AI progress.

As tech companies and pro-business entities laud Trump’s deregulation efforts, concerns persist over the societal impacts of such policies.

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China issues action plan for global AI governance and proposes global AI cooperation organisation

At the 2025 World AI Conference in Shanghai, Chinese Premier Li Qiang urged the international community to prioritise joint efforts in governing AI, making reference to a need to establish a global framework and set of rules widely accepted by the global community. He unveiled a proposal by the Chinese government to create a global AI cooperation organisation to foster international collaboration, innovation, and inclusivity in AI across nations.

‘China attaches great importance to global AI governance, and has been actively promoting multilateral and bilateral cooperation with a willingness to offer more Chinese solutions‘.

An Action Plan for AI Global Governance was also presented at the conference. The plan outlines, in its introduction, a call for ‘all stakeholders to take concrete and effective actions based on the principles of serving the public good, respecting sovereignty, development orientation, safety and controllability, equity and inclusiveness, and openness and cooperation, to jointly advance the global development and governance of AI’.

The document includes 13 points related to key areas of international AI cooperation, including promoting inclusive infrastructure development, fostering open innovation ecosystems, ensuring high-quality data supply, and advancing sustainability through green AI practices. It also calls for consensus-building around technical standards, advancing international cooperation on AI safety governance, and supporting countries – especially those in the Global South – in ‘developing AI technologies and services suited to their national conditions’.

Notably, the plan indicates China’s support for multilateralism when it comes to the governance of AI, calling for an active implementation of commitments made by UN member states in the Pact for the Future and the Global Digital Compact, and expressing support for the establishment of the International AI Scientific Panel and a Global Dialogue on AI Governance (whose terms of reference are currently negotiated by UN member states in New York).

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UBTech’s Walker S2 marks a leap towards uninterrupted robotic work

The paradigm of robotic autonomy is undergoing a profound transformation with the advent of UBTech’s new humanoid, the Walker S2. Traditionally, robots have been tethered to human assistance for power, requiring manual plugging in or lengthy recharges.

UBTech, a pioneering robotics company, is now dismantling these limitations with a groundbreaking feature in the Walker S2: the ability to swap its battery autonomously. The innovation promises to reshape the landscape of factory work and potentially many other industries, enabling near-continuous, 24/7 operation without human intervention.

The core of this advancement lies in the Walker S2’s sophisticated self-charging mechanism. When a battery begins to deplete, the robot does not power down. Instead, it intelligently navigates to a strategically placed battery swap station.

Once positioned, the robot executes a precise sequence of movements: it twists its torso, deploys built-in tools on its arms to unfasten and remove the drained battery from its back cavity, places it into an empty bay on the swap station, and then expertly retrieves a fresh, fully charged module.

The new battery is then securely plugged into one of its dual battery bays. The process is remarkably swift, taking approximately three minutes, allowing the robot to return to its tasks almost immediately.

The hot-swappable system mirrors the convenience of advanced electric vehicle technology, but its application to humanoid robotics unlocks unprecedented operational efficiency. Standing at 5 feet, 3 inches (approximately 160 cm) tall and weighing 95 pounds (about 43 kg), the Walker S2 is designed to integrate seamlessly into environments built for humans.

It has two 48-volt lithium batteries, ensuring a continuous power supply during the brief swapping procedure. While one battery powers the robot’s ongoing operations, the other can be exchanged.

Each battery provides approximately two hours of operation while walking or up to four hours when the robot stands still and performs tasks. The battery swap stations are not merely power hubs; they also meticulously monitor the health of each battery.

Should a battery show signs of degradation, a technician can be alerted to a timely replacement, further optimising the robot’s longevity and performance.

UBTech claims the Walker S2 is not a mere laboratory prototype but a robust solution engineered for real-world industrial deployment. Extensive testing has been conducted in the highly demanding environments of car factories operated by major Chinese electric vehicle manufacturers, including BYD, Nio, and Zeekr.

The trials validate the robot’s ability to operate effectively in dynamic production lines. The Walker S2 incorporates advanced vision systems, allowing it to detect battery levels and identify fully charged units, indicated by a green light on the stacked battery packs.

The robot autonomously reads the visual cues, ensuring precise selection and connection via a simple USB-style connector. Furthermore, the robot features a display face, enabling it to communicate its operational status to human workers, fostering a collaborative and transparent work environment. For safety, a prominent emergency stop button is also integrated.

China’s strategic investment in robotics is a driving force behind such innovations. Shenzhen, UBTech’s home base, is a thriving hub for robotics, boasting over 1,600 companies in the sector.

The nation’s broader push towards automation, part of its ‘Made in China 2025’ strategy, is a clear statement of global competitiveness, with China betting on AI and robotics to spearhead the next manufacturing era.

The coordinated industrial policy has led to China becoming the world’s largest market for industrial robots and a significant innovator in the field. The implications of robots like the Walker S2, built for non-stop operation, extend far beyond traditional factory floors.

Their ability to manage physical tasks continuously could redefine work in various sectors. Industries such as logistics, with vast warehouses requiring constant material handling, or airports, where baggage and cargo movement is ceaseless, benefit immensely.

Hospitals could also see these humanoids assisting with logistical duties, allowing human staff to concentrate on direct patient care. For businesses, the promise of 24/7 automation translates directly into increased output without additional human resources, ensuring operations move seamlessly day and night.

The Walker S2 exemplifies how advanced automation rapidly moves beyond research labs into practical, demanding workplaces. With its autonomous battery-swapping capability, humanoid robots are poised to work extended hours that far exceed human capacity.

The robots do not require coffee breaks or need sleep; they are designed for relentless productivity, marking a significant step towards a future where machines play an even more integral role in daily industrial and societal functions.

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Democratising clean energy through digital tokens

Tokenisation can remove barriers to green energy investment, allowing more involvement beyond institutional players, says Mete Al, Co-founder of ICB Labs.

Individuals could invest smaller sums and earn passive income by turning assets like solar farms into fractional digital tokens. It allows them to support renewable energy without owning physical infrastructure.

High costs and trust issues limit access to sustainable projects, but blockchain tools can boost confidence and ensure fair rewards.

ICB Labs is already working on a tokenised solar project for 2026. Al emphasises that strong governance and flexible regulation, including regulatory sandboxes, are essential to support innovation in decentralised climate finance.

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AI startup Daydream revolutionises online fashion search

Online shopping for specific items like bridesmaid dresses can be challenging due to overwhelming choices. A new tech startup, Daydream, aims to simplify this. It uses AI to let users search for products by describing them in natural language, making the process easier and more intuitive.

For instance, a user could ask for a ‘revenge dress to wear to a party in Sicily in July,’ or ‘a summer bag to carry to work and cocktails after.’

Daydream, with staff based in New York and San Francisco, represents the latest venture in a growing trend of tech companies utilising AI to streamline and personalise online retail.

Consumer demand for such tools is evident: an Adobe Analytics survey of 5,000 US consumers revealed that 39% had used a generative AI tool for online shopping last year, with 53% planning to do so this year. Daydream faces competition from tech giants already active in this space.

Meta employs AI to facilitate seller listings and to target users with more relevant product advertisements. OpenAI has launched an AI agent capable of shopping across the web for users, and Amazon is trialling a similar feature.

Google has also introduced various AI shopping tools, including automated price tracking, a ‘circle to search’ function for identifying products in photos, and virtual try-on options for clothing.

Despite the formidable competition, Daydream’s CEO, Julie Bornstein, believes her company possesses a deeper understanding of the fashion and retail industries.

Bornstein’s extensive background includes helping build Nordstrom’s website as its vice president of e-commerce in the early 2000s and holding C-suite positions at Sephora and Stitch Fix. In 2018, she co-founded her first AI-powered shopping startup, The Yes, which was sold to Pinterest in 2022.

Bornstein asserts, ‘They don’t have the people, the mindset, the passion to do what needs to be done to make a category like fashion work for AI recommendations.’ She added, ‘Because I’ve been in this space my whole career, I know that having the catalogue with everything and being able to show the right person the right stuff makes shopping easier.’

Daydream has already secured $50 million in its initial funding round, attracting investors such as Google Ventures and model Karlie Kloss, founder of Kode With Klossy. The platform operates as a free, digital personal stylist.

Users can input their desired products using natural language, eliminating the need for complex Boolean search terms, thanks to its AI text recognition technology, or upload an inspiration photo.

Daydream then presents recommendations from over 8,000 brand partners, ranging from budget-friendly Uniqlo to luxury brand Gucci. Users can further refine their search through a chat interface, for example, by requesting more casual or less expensive alternatives.

As users interact more with the platform, it progressively tailors recommendations based on their search history, clicks, and saved items.

When customers are ready to purchase, they are redirected to the respective brand’s website to complete the transaction, with Daydream receiving a 20% commission on the sale.

Unlike many other major e-commerce players, Bornstein is deliberately avoiding ad-based rankings. She aims for products to appear on recommendation pages purely because they are a suitable match for the customer, not due to paid placements.

Bornstein stated, ‘As soon as Amazon started doing paid sponsorships, I’m like, ‘How can I find the real good product?’ She emphasised, ‘We want this to be a thing where we get paid when we show the customer the right thing.’

A recent CNN test of Daydream yielded mixed results. A search for a ‘white, fitted button-up shirt for the office with no pockets’ successfully returned a $145 cotton long-sleeve shirt from Theory that perfectly matched the description.

However, recommendations are not always flawless. A query for a ‘mother of the bride dress for a summer wedding in California’ presented several slinky slip dresses, some in white, alongside more formal styles, appearing more suitable for a bachelorette party.

Bornstein confirmed that the company continuously refined its AI models and gathered user feedback. She noted, ‘We want data on what people are doing so we can focus and learn where we do well and where we don’t.’

Part of this ongoing development involves training the AI to understand nuanced contextual cues, such as the implications of a ‘dress for a trip to Greece in August’ (suggesting hot weather) or an outfit for a ‘black-tie wedding’ (implying formality).

Daydream’s web version launched publicly last month, and it is currently in beta testing, with plans for an app release in the autumn. Bornstein envisions a future where AI extends beyond shopping, assisting with broader fashion needs like pairing new purchases with existing wardrobe items.

She concluded, ‘This was one of my earliest ideas, but I didn’t know the term (generative AI) and I didn’t know a large language model would be the unlock.’

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AI chatbot captures veteran workers’ knowledge to support UK care teams

Peterborough City Council has turned the knowledge of veteran therapy practitioner Geraldine Jinks into an AI chatbot to support adult social care workers.

After 35 years of experience, colleagues frequently approached Jinks seeking advice, leading to time pressures despite her willingness to help.

In response, the council developed a digital assistant called Hey Geraldine, built on the My AskAI platform, which mimics her direct and friendly communication style to provide instant support to staff.

Developed in 2023, the chatbot offers practical answers to everyday care-related questions, such as how to support patients with memory issues or discharge planning. Jinks collaborated with the tech team to train the AI, writing all the responses herself to ensure consistency and clarity.

Thanks to its natural tone and humanlike advice, some colleagues even mistook the chatbot for the honest Geraldine.

The council hopes Hey Geraldine will reduce hospital discharge delays and improve patient access to assistive technology. Councillor Shabina Qayyum, who also works as a GP, said the tool empowers staff to help patients regain independence instead of facing unnecessary delays.

The chatbot is seen as preserving valuable institutional knowledge while improving frontline efficiency.

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Z.ai unveils cheaper, advanced AI model GLM-4.5

Chinese AI startup Z.ai, formerly Zhipu, is increasing pressure on global competitors with its latest model, GLM-4.5. The company has adopted an aggressive open-source strategy to attract developers. Anyone can download and use the model without licensing fees or platform restrictions.

GLM-4.5 is designed with agentic AI, breaking tasks into smaller components for improved performance. By approaching problems step by step, the model delivers more accurate and efficient outcomes. Z.ai aims to stand out through both technical sophistication and affordability.

CEO Zhang Peng says the model runs on only eight Nvidia H20 chips, while DeepSeek’s model needs sixteen. Nvidia developed the H20 to comply with US export controls aimed at China. Reducing chip demand significantly lowers the model’s operational footprint.

Zhang said the company has enough computing power and is not seeking further hardware now. Z.ai plans to charge 11 cents per million input tokens, undercutting DeepSeek R1’s 14 cents. Output tokens will cost 28 cents per million, compared to DeepSeek’s 2.19 dollars.

Such pricing could reshape large language model deployment expectations, especially in resource-limited environments. High costs have long been a barrier to broader AI adoption. Z.ai appears to be positioning itself as a more accessible alternative.

Founded in 2019, Z.ai has raised more than 1.5 billion dollars from investors including Alibaba, Tencent, and Qiming Venture Partners. It has grown quickly from a research-focused lab to one of China’s most prominent AI contenders. A public listing in Greater China is reportedly being prepared.

OpenAI recently named Zhipu among the Chinese firms it considers strategically significant in global AI development. US authorities responded by restricting American companies from working with Z.ai. The startup has nonetheless continued to expand its model lineup and partnerships.

Chinese firms increasingly invest in open-source models, often with domestic hardware compatibility in mind. Moonshot, another Alibaba-backed company, released the Kimi K2 model. Kimi K2 has received praise for its performance in coding and mathematical tasks.

Tencent has joined the race with its HunyuanWorld-1.0 model, which is built to generate immersive 3D environments. The HunyuanWorld-1.0 can accelerate game development, virtual reality design, and simulation work. Cutting-edge features are being paired with highly efficient architectures.

Alibaba also introduced its Qwen3-Coder model to assist in code generation and debugging. Such AI tools are seeing increasing use in software engineering and education. Chinese developers are positioning themselves to compete with Western offerings such as OpenAI’s Codex and Anthropic’s Claude.

The momentum within China’s AI sector is accelerating despite geopolitical and trade restrictions. A clear shift is underway from imitation to innovation, with local startups advancing independent research. Many models are trained on China-specific datasets to optimise relevance and performance.

Z.ai’s strategy combines cost reduction, efficient chip use, and broad availability. The company can build community trust and encourage ecosystem growth by open-sourcing its tools. At the same time, pricing undercuts major rivals and could disrupt the market.

Global AI development is increasingly decentralised, with Chinese firms no longer just playing catch-up. Large-scale funding and state support are helping to close gaps in hardware and training infrastructure. Z.ai is one of several firms pushing toward greater technological autonomy.

Open-source AI development is also helping Chinese companies win favour with developers outside their borders. Many international teams are experimenting with Chinese models to diversify risk and reduce reliance on US tech. Z.ai’s GLM-4.5 is among the models gaining traction globally.

By offering a powerful, lightweight, and affordable model, Z.ai is setting a new benchmark in the industry. The combination of technical refinement and strategic pricing draws attention from investors and users. A new era of AI competition is emerging.

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New AI model, Aeneas, assists historians in interpreting Roman inscriptions

Thanks to AI, historians studying ancient Rome now have a powerful new tool.

A research team, including scholars from Google DeepMind and the University of Nottingham, developed a generative AI model called Aeneas that can help interpret damaged Latin inscriptions by estimating their location and date and suggesting likely missing text.

Each year, roughly 1,500 new Latin inscriptions are unearthed, ranging from imperial decrees to everyday graffiti. These inscriptions, written by ancient Romans across all social classes, offer rare, first-hand insights into daily life, language, and society.

Yet many of them are incomplete or difficult to contextualise. Traditionally, scholars must compare each inscription against hundreds of others manually — a process described as laborious and requiring exceptional expertise.

Aeneas, trained on over 170,000 Latin texts, can now predict when and where an inscription was written across the Roman Empire’s 62 provinces. In one test case, it analysed the famous Res Gestae Divi Augusti, narrowing down the date to the same two options long debated by historians.

Aeneas significantly improved research outcomes when used alongside human expertise instead of replacing it, helping scholars piece together history more efficiently than ever.

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Viasat launches global IoT satellite service

Viasat has unveiled a new global connectivity service designed to improve satellite-powered internet of things (IoT) communication, even in remote environments. The new offering, IoT Nano, supports industries like agriculture, mining, transport with reliable, low-data and low-power two-way messaging.

The service builds on Orbcomm’s upgraded OGx platform, delivering faster message speeds, greater data capacity and improved energy efficiency. It maintains compatibility with older systems while allowing for advanced use cases through larger messages and reduced power needs.

Executives at Viasat and Orbcomm believe IoT Nano opens up new opportunities by combining wider satellite coverage with smarter, more frequent data delivery. The service is part of Viasat’s broader effort to expand its scalable and energy-efficient satellite IoT portfolio.

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Meta forms AI powerhouse by appointing Shengjia Zhao as chief scientist

Meta has appointed former OpenAI researcher Shengjia Zhao as Chief Scientist of its newly formed AI division, Meta Superintelligence Labs (MSL).

Zhao, known for his pivotal role in developing ChatGPT, GPT-4, and OpenAI’s first reasoning model, o1, will lead MSL’s research agenda under Alexandr Wang, the former CEO of Scale AI.

Mark Zuckerberg confirmed Zhao’s appointment, saying he had been leading scientific efforts from the start and co-founded the lab.

Meta has aggressively recruited top AI talent to build out MSL, including senior researchers from OpenAI, DeepMind, Apple, Anthropic, and its FAIR lab. Zhao’s presence helps balance the leadership team, as Wang lacks a formal research background.

Meta has reportedly offered massive compensation packages to lure experts, with Zuckerberg even contacting candidates personally and hosting them at his Lake Tahoe estate. MSL will focus on frontier AI, especially reasoning models, in which Meta currently trails competitors.

By 2026, MSL will gain access to Meta’s massive 1-gigawatt Prometheus cloud cluster in Ohio, designed to power large-scale AI training.

The investment and Meta’s parallel FAIR lab, led by Yann LeCun, signal the company’s multi-pronged strategy to catch up with OpenAI and Google in advanced AI research.

The collaboration dynamics between MSL, FAIR, and Meta’s generative AI unit remain unclear, but the company now boasts one of the strongest AI research teams in the industry.

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